Location: Plant Science Research
Title: Using RNA-Seq for gene identification, polymorphism detection and transcript profiling in two alfalfa genotypes with divergent cell wall composition in stems Authors
|Tu, Zheng Jin -|
|Foo, Cheung -|
|Xu, Wayne Wenzhong -|
|Jung, Hans Joachim|
Submitted to: Biomed Central (BMC) Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 19, 2011
Publication Date: April 19, 2011
Repository URL: http://hdl.handle.net/10113/53778
Citation: Yang, S.H., Tu, Z., Foo, C., Xu, W., Lamb, J.F., Jung, H.G., Vance, C.P., Gronwald, J.W. 2011. Using RNA-Seq for gene identification, polymorphism detection and transcript profiling in two alfalfa genotypes with divergent cell wall composition in stems. Biomed Central (BMC) Genomics. 12:199. Available: http://www.biomedcentral.com/1471-2164/12/199. Interpretive Summary: There is a need to reduce U.S. dependence on foreign oil imports. Developing cellulosic feedstocks to be used for ethanol production addresses this need. Alfalfa, a widely-grown forage, offers considerable potential as a bioenergy crop. One advantage of alfalfa over other potential cellulosic feedstocks is that it is able to fix (scrub) nitrogen from the air and hence does not need added nitrogen fertilizer. We envision that alfalfa would be a dual-purpose bioenergy crop. Alfalfa stems would be used for ethanol production while the leaves would be used as a high-value livestock feed. Modifying the cell wall composition of alfalfa stems (increasing cellulose, decreasing lignin) would increase ethanol yield. Genes that regulate lignin and cellulose levels in alfalfa stems need to be identified so that plant breeders and molecular biologists can develop alfalfa cultivars with higher ethanol yield. However, the genomics of alfalfa, a non-model plant species, is still in its infancy. Few genes have been identified in alfalfa. The recent advent of RNA-sequencing (RNA-Seq) technology involving ultra-high throughput sequencing provides an opportunity to significantly increase the number of genes identified in alfalfa and to conduct in-depth measurements of gene expression in alfalfa. We performed RNA-Seq analysis of the stems of two alfalfa cultivars that differ in cell wall concentrations of lignin and cellulose. The analysis resulted in the identification of thousands of new ESTs (gene tags). By combining these results with ESTs that we previously identified and the ESTs in the public database, we developed the first Alfalfa Gene Index (MSGI 1.0). Analysis of gene expression in the stems of the two alfalfa cultivars that differ in cell wall lignin and cellulose concentrations resulted in the identification of several candidate genes that may regulate lignin and cellulose biosynthesis. Overall, the results of this research provide a significant advance in knowledge of alfalfa genomics. This knowledge and the genes identified can be used by plant breeders and molecular biologists to improve alfalfa as a bioenergy crop.
Technical Abstract: Alfalfa [Medicago sativa (L.) sativa], a widely-grown perennial forage, has potential for development as a cellulosic feedstock for ethanol production. Identifying key genes regulating lignin and cellulose biosynthesis in alfalfa would advance its development as a cellulosic feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analyses, provides an opportunity to expand the identification of alfalfa genes and conduct in-depth transcript profiling. Cell walls of stems of alfalfa genotype 773 have high lignin and low cellulose concentrations, while cell walls of stems of genotype 708 have low lignin and high cellulose concentrations. Using Solexa GA-II, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 773 and 708. These ESTs were de novo assembled into 132,153 unique sequences. By combining the de novo assembled ESTs (132,153 sequences) with our previously identified EST sequences (341,984 sequences, unpublished data), and the ESTs available from GenBank (12,371 sequences), we built the first Alfalfa Gene Index (MSGI 1.0). MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons, and 78,981 pseudo-singletons. Transcript profiling of stem internodes of alfalfa genotypes 773 and 708 was conducted by quantifying the number of 76 bp reads that were mapped to the MSGI 1.0 sequences. We identified numerous candidate genes that may contribute to the differences in cell wall lignin and cellulose concentrations in stems of the two genotypes. For example, caffeic acid O-methyl transferase (COMT) genes involved in lignin biosynthesis were up-regulated in genotype 773 (high-lignin) compared to genotype 708 (low-lignin). We also identified numerous genes that may be involved in general stem development independent of genotypic variation. Real-time quantitative RT-PCR (qRT-PCR) of both randomly-selected genes and several selected candidate genes validated the transcript profiling data. We identified a large number of simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, many SNPs were predicted between the two genotypes. Our results demonstrate that RNA-Seq can be successfully used for gene identification, transcript profiling, and polymorphism detection in a non-model species such as alfalfa.